Off-season tourists and the cultural offer of a mass-tourism destination: The case of Rimini

TL;DR: In this paper, the authors assess the potential implications on off-season tourism of enhancing the cultural offer of Rimini, a popular Italian seaside holiday destination hosting about 12 million overnight stays per year.

About: This article is published in Tourism Management.The article was published on 2012-08-01 and is currently open access. It has received 79 citations till now. The article focuses on the topics: Cultural tourism & Business tourism.

Summary

1 Introduction

• Cultural tourism is an important topic, lying at the cornerstone of cultural and tourism economics and constituting the motivation for a vast and growing scientific production.
• In tourism economics, cultural tourism is often recalled as the main tool used to counteract seasonality in destinations and to overcome problems related to the maturity stage of their life-cycle.
• In particular, the paper assesses the potential implications on off-season tourism of enhancing the cultural (and leisure) offer of Rimini.

2 The methodology and the survey

• The choice modelling is a stated-preference approach which investigates individual behaviour and estimates the value of goods (or projects) by asking people to choose among scenarios which differ for the combination of alternative levels of some selected attributes .
• One of the advantages of choice experiments lies in their ability to model individuals’ hypothetical demand for non-market goods.
• The questionnaire was designed to gather information on off-season tourists perception of actual or hypothetical "holiday packages" offered by the territory of Rimini for leisure and cultural activities.
• These estimates rely on the assumption that the marginal utility of income is constant: this holds only when small changes are considered (involving a tiny share of total individual income).
• The interviews were hence split into four groups whose respondents had to answer to different sets of 8 choice cards with different pairs of hypothetical alternative scenarios.

3 Tourists’ demographic and social characteristics

• Secondly, as regards the educational background, the authors found that 15% of the respondents hold a primary degree, 44.3% a secondary degree, while 40.7% a University degree.
• In order to make clear and homogeneous the comprehension of attributes and to facilitate the individual decision process, the oral explanation of these attributes and levels was accompanied by the presentation of drawings and photos describing each scenario.
• Finally, almost all business travelers (89.5%) let the company organize the trip (even through a tour operator), although there is a relevant share (10.5%) who self-organized it.
• 6% of those who previously visited Rimini, 24.2% of the sample did it for leisure activities during the summer months only, and a high share of respondents (37.6%) previously stayed in Rimini for both leisure and non-leisure reasons.

3.1 Tourism market segments and latent class analysis

• In the previous section, the authors described and classified tourists on the basis of observable and characterizing variables, and directly asking what is the main reason for their visit to Rimini.
• For this reason, the questionnaire was built in a way to endogenously identify different segments of tourism through a latent class analysis.
• The technique allowed us to extract from data some common factors, in order to reduce the number of explanatory variables which may impact the choice.
• This factor mainly affects women who recognize in cultural events the main motivation of their stay in Rimini and is significantly correlated with tourists lodging in 4-5 star hotels and with people with higher income.
• “Leisure lovers” (66.76% of their sample): tourists who are mainly interested in sport and wellness facilities and are only slightly affected by the cultural offer.

4.1 The conditional logit model

• Table 6 presents the results of a conditional logit model estimated for the whole sample and for four subsamples based on whether the trip's main reason is business, cultural, leisure or other.
• As a check on the role played by time, the authors re-run the model with the time value also inserted as series of dummies (Table 7).
• The coefficient for the dummy related to two nights more, however, was not significant.
• Robust results emerged, with important policy implications: firstly, business and leisure tourists, differently from cultural tourists, were not interested in organized trips in the surroundings of Rimini and in discovering their beauty in terms of cultural heritage, food and wine resources and landscape.

4.2 The in-deep analysis: the model applied to different sub-samples

• Firstly, the authors split according to the region of origin of tourists (Italians and Foreigners).
• The main difference is related to the importance of organized trips (the coefficient was not significant for Foreigners) and to the time attribute (none of the coefficients of the time dummies are significant for Foreigners: clearly, they are not willing to spend more time in Rimini.
• Finally, with respect to the time dummies, the only significant coefficients were for the adults (who were willing to stay one more night) and for the elderly (who were willing to stay two more nights, probably because of their loose time constraint).
• In Table 9, other break-downs of the whole sample were proposed.
• Leisure lovers are willing to spend more time in the same location, to do shopping even during the night and on Sundays and to access wellness facilities.

5 Choice probability of different scenarios and policy discussion

• Choice experiments can help policy makers since it is possible to create alternative hypothetical scenarios by mixing attribute levels.
• It has to be recalled that this simulation, which considers more than two alternatives at the same time, is based on the IIA assumption.
• There is one important difference among business and leisure tourists, which lies in their second best: for business tourists it was the environmental scenario, while for leisure 30The probability that an individual picked each scenario out of the four alternatives was computed by inserting in equation (2.2) the coefficient estimated in Tables 7. tourists it was the cultural scenario.
• The least preferred scenario is, by all groups, the status quo: indeed, there is room for improvements in the organization of Rimini's tourism policy.
• Alternatively, if a budget constraint is active in the destination, it appears that the policy makers have to choose between two opposite models of off-season tourism development: the cultural and the leisure model.

5.1 Choice probability of different scenarios

• As recalled in the introduction, their analysis follows two studies which, using the same methodology and a very similar questionnaire, were investigating summer tourists’ preferences in Rimini (Brau et al. 2009) and residents of the city of Rimini (Figini et al. 2009).
• This simulation allows the identification of differences in the distribution of tourists and residents’ preferences among alternative scenarios, and the identification of the preferred scenarios for residents and for different types of tourists.
• Moreover, it provides useful information for policy makers aiming at proposing social welfare enhancing tourism projects.
• The inspection of Table 12 shows that the status quo was always the worst scenario for all types of tourists and for residents.
• Again, policy makers seem to be facing a strong trade-off between the use of the territory and the demands and needs of "hosts" and "guests" of Rimini.

6 Conclusions

• In this paper the authors attempted to check for any synergy and trade-off arising among different types of offseason tourists in a mass tourism destination.
• In the case of a mature destination such as Rimini, which recently made a great effort in diversifying mainly towards business and cultural tourism, this issue is crucial for both the tourism and the cultural policy of the territory.
• These are the main questions the authors addressed with this work.
• Moreover, in order to win the strong competition with other Italian cultural destinations, investments have to be directed towards contemporary art.

Figures

Figure 1: Factor scores for each cluster

Table 3. Demographic and socio-economic characteristics of the sample

Table 10. Estimation of conditional logit model: different sub-samples

Table 11. Simulation of the distribution of choice probabilities in the case of four scenarios

Table 12. Simulation of the distribution of choice probabilities in the case of four scenarios for residents, in-season and off-season tourists.

Table 5. Previous and Future trips to Rimini.

Table 8. Estimation of conditional logit model: different sub-samples

Table 7 Estimation of conditional logit model: whole sample, business tourism, cultural tourism, leisure tourism and other tourism (time attribute inserted as a series of dummy variables).

Table 4. Main characteristics of the trip

Table 2. Definition of attributes and their levels

Table 9. Estimation of conditional logit model: different sub-samples

Table 1. Arrivals, Overnight stays and Length of Stay of Italian and Foreign Tourists in the province of Rimini (1972 - 2007, thousands).

Table 6 Estimation of conditional logit model: whole sample, business tourism, cultural tourism, leisure tourism and other tourism (time attribute inserted in cardinal numbers)